Dr Mark Dunning PhD

Bioinformatics Core Director

Research Interests

High-throughput technologies such as next generation sequencing (NGS) can routinely produce massive amounts of data that can be used for tasks such as identifying biological samples with aberrant expression patterns or allow us to describe all variants in a genome. However, such datasets pose new challenges in the way the data have to be analyzed, annotated and interpreted which are not trivial and are daunting to the wet-lab biologist. My interests lie in making the analysis of high-throughput datasets accessible to the non-bioinformatician; via specialised training courses and by developing computational pipelines and workflow. I am currently exploring technologies that facilitate reproducible research and promote an open attitude to scientific research, and endeavour to make my talks, code, and analyses available whenever.

Current Projects

From October 2017 I will be establishing a Bioinformatics Core service at The University of Sheffield to support researchers in the planning, analysis, interpretation and management of their data. I will also be developing and organising training courses covering the analysis skills essential to the being a modern, data-literate scientist

2004 – 2005: Msc (Data Analysis, Networks and Nonlinear Dynamics) University of York

1999 – 2004: Bsc (Mathematics and Computer Science) University of York

I obtained my PhD in the Statistics and Computational Biology group of Simon Tavare at The University of Cambridge. As part of my thesis I developed open-source software for the analysis of Illumina microarray data, which is available through the Bioconductor project. I joined the Bioinformatics Core at Cancer Research Uk Cambridge Institute and played a key role in the analysis of gene expression profiles as part of the METABRIC project, which identified and described new subtypes of breast cancer. I also participated in the pilot phases of the International Cancer Genome Consortium (ICGC) project by developing computational pipelines to process the whole-genome sequencing data from Oesophageal cancer patients. During my time in the Bioinformatics Core I also developed a passion for teaching and commenced a role dedicated to organising and delivering Bioinformatics training courses, with the aim of empowering wet-lab scientists to begin to explore data for themselves and foster more-productive collaborations with Bioinformaticians.

I have a strong commitment to reproducible research and making my research outputs available to other researchers, and indeed members of the public who may have funded the research in the first place. For instance, I recently developed and deployed a Shiny application that allows interested parties to query various prostate cancer datasets. In keeping with my open access principles, the code underlying the application is available via github and utilises data sets that can be downloaded from Bioconductor. I have also recently investigated technologies such as Galaxy and Docker to ease the deployment of software and facilitate reproducible research.